A Comparison of Regular and Thermal Cameras for Traffic Data Collection under Varying Lighting and Temperature Conditions in Multimodal Environments

Collecting traffic data was traditionally limited to technologies such as inductive loops at fixed locations, though loops do not capture all road user types. Vision-based monitoring systems using simple video cameras can complement or substitute conventional sensors and provide rich positional and classification data. Recently, new camera technologies, including thermal cameras, have become available and may improve the performance of digital video-based sensors. However, the performance of thermal cameras under various lighting and temperature conditions has rarely been evaluated at multimodal facilities including intersections, where road user classification is required. The purpose of this study is to evaluate the performance of thermal video sensors under varying lighting and temperature conditions for the detection, classification, and speed measurement of road users. For this purpose, thermal and regular video data was collected simultaneously under different conditions across multiple sites. The regular camera narrowly outperformed the thermal camera in terms of detection and classification of all road users during daytime conditions. However, the detection rate dropped significantly for pedestrians and cyclists at night for the regular camera. Importantly, the thermal video performs acceptably during daytime, with a miss rate around 5%. Speed measurements by the thermal camera were consistently more accurate than for the regular video at daytime and nighttime. The thermal videos are insensitive to lighting interference and pavement temperature, and solve the issues associated with visible light cameras for traffic data collection, especially for pedestrians and cyclists.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ABJ35 Standing Committee on Highway Traffic Monitoring.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Fu, Ting
  • Stipancic, Joshua
  • Zangenehpour, Sohail
  • Miranda-Moreno, Luis
  • Saunier, Nicolas
• Conference:
  • Transportation Research Board 95th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2016-1-10 to 2016-1-14
• Date: 2016

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 18p
• Monograph Title: TRB 95th Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Automatic data collection systems; Computer vision; Detection and identification systems; Lighting; Performance measurement; Thermal imagery; Video cameras
• Subject Areas: Data and Information Technology; Highways; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01590327
• Record Type: Publication
• Report/Paper Numbers: 16-2846
• Files: TRIS, TRB, ATRI
• Created Date: Feb 16 2016 3:31PM